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Computing That Serves

Graduate Policy Handbook - Appendix

Forms

The following is a partial list of the most common forms used by graduate students. Graduate Studies has a complete list of forms available on their Web site. Please contact the CS Graduate Program Manager if you have any questions regarding forms.

 

Submitting an ETD

  • Submitting an ETD (be sure to include bookmarks for ALL pages preceding your table of contents and then use your table of contents as a guide for all the other pages that need to be bookmarked)

 

Tentative 5 Year Schedule of CS Courses Offerings

 

Computer Science Graduate Courses

  • 557. Computer-Aided Geometric Design. (3) Prerequisite: CS 240, Math 343; or equivalents.
    Free-form curves and surfaces: mathematical theory and algorithms. Bezier and B-spline curves and surfaces, subdivision surfaces, T-splines, free-form deformation, and intersection algorithms. Several programming projects.
  • 579. Natural Language Processing. (3) Prerequisite: instructor's consent.
    Machine translation, human-computer dialog, question answering, parsing, and generating from an artificial intelligence and machine learning perspective.
  • 586. Multiprocessor programming and verification. (3) Prerequisite: CS 312 
    Concurrency theory and practical application of concurrent programming for shared memory systems including coarse grain locking, fine grain locking, optimistic locking, lock-free constructs, and wait-free constructs.
  • 598R. Special Projects. (1-3) Prerequisite: instructor's consent.
  • 601R. Special Topics in Computer Science. (1-3) Prerequisite: instructor's consent.
    Subjects as announced before each semester.
  • 611. Theoretical Foundations of Computing. (3) Prerequisite: CS 252 or equivalent; CS 312 or instructor's consent.
    Proofs (deductive and inductive reasoning), computability (models of computability and computability issues), and complexity (time and space bounds, nondeterminism, and complexity classification).
  • 621. Pattern Recognition. (3) Prerequisite: CS 450 or equivalent.
    Design and use of pattern classifiers for recognition and classification of one- and two-dimensional signals such as voice, images, and handwriting. Emphasis on images.
  • 650. Computer Vision 1. (3) Prerequisite: CS 450 or equivalent.
    Machine vision, image segmentation, mathematical morphology, image enhancement and filtering, edge detection, feature extraction, neighborhood operators, region growing, boundary detection, scene segmentation, and matching.
  • 651. Theoretical Foundations of Object-Oriented Data Engineering. (3) Prerequisite: CS 452 or instructor's consent.
    Applying model and proof theory to object-oriented database development and data engineering; construction of theory-based tools; conceptual model formalization; topics of current interest.
  • 652. Information Extraction and Integration. (3) Prerequisite: CS 452 (or equivalent) and/or 553.
    Information extraction from structured, semi-structured, and unstructured documents, including Web documents; integrating heterogeneous source information; theoretical foundations of information modeling; topics of current interest.
  • 653. Information Retrieval. (3) Prerequisite: CS 236 or equivalent.
    IR modeling, IR query languages, text indexing and searching, retrieval evaluation, query and text operations, parallel and distributed IR, Web searching.
  • 655. Advanced Computer Graphics. (3) Prerequisite: CS 455 or instructor's consent.
    Advanced computer graphics systems programming and architecture, including ray tracing, radiosity, animation, and physically based modeling.
  • 656. Interactive Software Systems. (3) Prerequisite: CS 330, 456; or instructor's consent.
    Advanced techniques for interacting with humans using pen-based, speech-based, hand-held, wall-sized, and room-sized devices. Embedding computing in everyday objects.
  • 660. Computer Networks. (3) Prerequisite: CS 460, Stat. 321; or equivalents.
    Computer networking, software architecture, organization protocols, routing, global networks, local networks, internetworking, standards, and applications.
  • 665. Advanced Computer Security. (3) Prerequisite: CS 465 or instructor's consent.
    Authentication and authorization using digital credentials.
  • 670. Multi-Agent Systems. (3) Prerequisite: CS 470 or equivalent; CS 478 or instructor's consent.
    Introduction to fundamental concepts emphasizing current literature. Topics include: game theory, repeated play games, Arrow's impossibility theorem, negotiation, search, and learning.
  • 673. Computational Creativity. (3) Prerequisite: CS 478 or CS 470 or instructor's consent.
    Introduction to the foundational literature in computational creativity; inter-disciplinary and synergistic, with a heavy emphasis on a course project whose goal is to produce a computational system to which creativity (in some form) can be attributed.
  • 677. Bayesian Methods in Computer Science. (3) Prerequisite: CS 470 or instructor's consent.
    Applying Bayesian methods useful for incorporating confidence or belief into problems in computer science, allowing computers to better handle uncertainty.
  • 678. Neural Networks and Machine Learning. (3) Prerequisite: CS 478 or equivalent.
    Advanced models, algorithms, and approaches in neural networks and machine learning.
  • 680. High Performance Computer Architecture. (3) Prerequisite: CS/EcEn 324 or equivalent.
    Advanced topics in computer architecture, including pipelining, super pipelining, VLIW, superscalar, branch prediction, and speculative execution.
  • 684. Parallel Processing. (3) Prerequisite: CS 324, 345, CS 380; or equivalent.
    Theoretical and practical study of parallel processing including a discussion of parallel architectures, parallel programming languages, and parallel algorithms.
  • 699R. Master's Thesis. (1-6) Prerequisite: committee chair's consent.
  • 750. Computer Vision 2. (3) Prerequisite: CS 650.
    Advanced topics in computer vision: Radiometric model; photometric stereo; shape from shading; monocular, binocular models; perspective projective geometry; image matching; depth from stereo; exterior, relative, interior absolute orientation; optical flow.
  • 751R. Advanced Topics in Database Systems. (3) Prerequisite: Graduate standing and instructor's consent.
  • 778R. Topics in Neural Networks and Machine Learning. (3) Prerequisite: CS 678.
    Advanced topics and readings in neural networks and machine learning.
  • 786R (Effective Fall 2004). Readings in Model Checking. (3) Prerequisite: CS 686.
    Focused readings and projects as suggested by class interest and current trends.
  • 799R. Doctoral Dissertation. (1-9) Prerequisite: committee chair's consent.